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“Getting started with Encord and integrating it into our workflow was really fast. The thing that I find the most valuable is the flexibility of how we can integrate the Encord pipeline into our own pipeline, we use the Python SDK a lot."
“Encord’s robust support system has been remarkable. Whenever questions or issues come up, they are always supportive and helpful. This ensures that our workflows remain uninterrupted."
Fiddler is a pioneer in Model Performance Management for responsible AI. The Fiddler platform’s unified environment provides a common language, centralized controls, and actionable insights to operationalize ML/AI with trust. Model monitoring, explainable AI, analytics, and fairness capabilities address the unique challenges of building in-house stable and secure MLOps systems at scale. Unlike observability solutions, Fiddler integrates deep XAI and analytics to help you grow into advanced capabilities over time and build a framework for responsible AI practices. Fortune 500 organizations use Fiddler across training and production models to accelerate AI time-to-value and scale, build trusted AI solutions, and increase revenue.
Seldon is a data science and machine learning operations platform on a mission to empower Data Scientists, ML Engineers, and MLOps teams to deploy, monitor, explain, and manage their ML models. With Seldon, organizations can minimize risk and drastically cut down time-to-value from their models organization offers both an open-source framework, Core, which focuses on model deployment, and an enterprise product, Deploy Advanced, which builds on this functionality to power model monitoring, explainability and management.
WhyLabs was started at the Allen Institute for AI by Amazon Machine Learning alums Alessya Visnjic, Sam Gracie, and Andy Dang, together with Maria Karaivanova, former Cloudflare executive. They are privately-held, venture-funded company based in Seattle. WhyLabs, they have their eyes set on an ambitious goal: to build the interface between humans and AI applications. They are starting with AI Observability. As teams across industries adopt AI, their Platform enables them to operate with certainty by providing model monitoring, preventing costly model failures, and facilitating cross-functional collaboration.
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